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D4Science is built and operated by relying on the gCube software system.
gCube is an open source software system specifically conceived to enable the creation and operation of Hybrid Data Infrastructures enabling Virtual Research Environments.
gCube offers a compelling portfolio of applications having vast and heterogeneous target audience ranging from scientists willing to perform their investigations in a more "simple" way to service providers willing to develop innovative facilities for scientists. The current catalogue of applications captures six main domain bundles that can be customized to meet specific needs.
AppsCube is for practitioners willing to develop web applications on the infrastructure. Applications are transparently enabled on a distributed and elastic infrastructure, their cost of maintenance are reduced, scalability, security, privacy and trustworthy are granted for free. With AppsCube there are no servers to maintain, it is just a matter of software configuration. AppCube supports Java-based applications and clients written in any language. It also embeds a thin layer to build portals able to easy connect to the infrastructure.
BiolCube is for practitioners willing to work with biological and ecological datasets, e.g. species occurrence data and taxonomic profiles. It helps them to access, download, compare, and generate new knowledge from this data (e.g. modeling and analyzing distribution data, comparing checklists, and producing maps). It interfaces with major data sources and information systems (e.g. OBIS, GBIF, Catalogue of Life).
ConnectCube is for practitioners willing to produce information-rich objects, resulting from the aggregation and synthesis of data from multiple sources. It offers a comprehensive tool suite, which supports a collaborative, standards-oriented data-publication environment, including semantic technologies. It enables to seamlessly discover research objects across diverse data sources including scientific repositories.
GeosCube is for practitioners willing to deal with geospatial information. It offers the facilities of a Spatial Data Infrastructure allowing to properly access, consume, and publish geospatial data compliant with the OGC standard formats and protocols. It allows to perform data processing tasks via Web Processing Service, as well as visualizing and publishing such data via state-of-the-art techniques (including Web Map Service, Web Feature Service). It enables easy-to-use rasterization and maps comparison.
IceCube is for practitioners willing to set up scalable data processing solutions with conceptually limited resources. It helps service providers willing to put in place innovative workflows and approaches for data processing by relying on the offering of a gCube-based underlying infrastructure. By using IceCube monitoring, accounting, and policy enforcement are granted for free.
StatsCube is for practitioners willing to deal with a rich array of information, ranging from observational data to statistical data. It is a complete data-life-cycle-supporting framework, including data access, validation, harmonization, enrichment, preparation, and efficient analysis. By using StatsCube it is possible to easily prepare the data and then process them with R by exploiting a powerful distributed and scalable computing infrastructure.